Quantifying stratigraphic uncertainty is crucial for reliable risk assessment and informed decision-making in geotechnical and geological engineering. However, accurately modeling complex stratigraphy ...

Abstract: Sparse matrix storage optimization is crucial in expanding the occurrences of datasets in scientific computation, machine learning, and high-dimensional applications, in which the ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...

Generative A.I. chatbots are going down conspiratorial rabbit holes and endorsing wild, mystical belief systems. For some people, conversations with the technology can deeply distort reality. By ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...

Gen Z-focused direct-to-consumer brand Freakins is raising Rs 25 crore (approximately $3 million) in its Series A round from existing investors Matrix Partners India and Blume Ventures. The board at ...

High sparse Knowledge Graph is a key challenge to solve the Knowledge Graph Completion task. Due to the sparsity of the KGs, there are not enough first-order neighbors to learn the features of ...

The Defense Advanced Research Projects Agency (DARPA) is taking a significant step toward overcoming the challenges of assembling large-scale structures in orbit by testing new in-space manufacturing ...

Rust Scientific Libary. ODE and DAE (Runge-Kutta) solvers. Special functions (Bessel, Elliptic, Beta, Gamma, Erf). Linear algebra. Sparse solvers (MUMPS, UMFPACK ...

Can the implicit solvers in diffrax use a sparse matrix solve for the jacobian? I'm putting together a benchmark with a few different ode solvers, including diffrax, and the problem in question is ...